Alternative pyramid wavefront sensors
Bibliographic record
Abstract
The feasibility of a lenslet-based pyramid wavefront sensor (L-PWFS) and a double roof prism-based PWFS (DR-PWFS) as alternatives to a classical PWFS are investigated in this work. Traditional PWFSs require shallow angles and strict apex tolerances, making them difficult to manufacture. Lenslet arrays and roof prisms, on the other hand, are both common optical components that can be used as a PWFS. Characterizing these alternative pyramids and understanding how they differ from a traditional pyramid will allow the PWFS to become more widely used. The sensitivity of the SUSS microOptics 300-4.7 array and two ios Optics roof prisms are compared with a double PWFS (D-PWFS), as well as the simulated performance of an idealized PWFS for varying amounts of modulation and induced wavefront error. In response to low-order Zernike modes, the L-PWFS shows much lower performance and quicker saturation for large amounts of wavefront errors. The DR-PWFS, on the other hand, performs as well as the D-PWFS for the tests conducted. We conclude from this that the DR-PWFS does provide a feasible alternative to the classical pyramid in a range of applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".